Literature DB >> 27878453

Evaluation of stability and validation of reference genes for RT-qPCR expression studies in rice plants under water deficit.

Priscila Ariane Auler1, Letícia Carvalho Benitez2, Marcelo Nogueira do Amaral2, Isabel Lopes Vighi2, Gabriela Dos Santos Rodrigues2, Luciano Carlos da Maia3, Eugenia Jacira Bolacel Braga2.   

Abstract

Many studies use strategies that allow for the identification of a large number of genes expressed in response to different stress conditions to which the plant is subjected throughout its cycle. In order to obtain accurate and reliable results in gene expression studies, it is necessary to use reference genes, which must have uniform expression in the majority of cells in the organism studied. RNA isolation of leaves and expression analysis in real-time quantitative polymerase chain reaction (RT-qPCR) were carried out. In this study, nine candidate reference genes were tested, actin 11 (ACT11), ubiquitin conjugated to E2 enzyme (UBC-E2), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), beta tubulin (β-tubulin), eukaryotic initiation factor 4α (eIF-4α), ubiquitin 10 (UBQ10), ubiquitin 5 (UBQ5), aquaporin TIP41 (TIP41-Like) and cyclophilin, in two genotypes of rice, AN Cambará and BRS Querência, with different levels of soil moisture (20%, 10% and recovery) in the vegetative (V5) and reproductive stages (period preceding flowering). Currently, there are different softwares that perform stability analyses and define the most suitable reference genes for a particular study. In this study, we used five different methods: geNorm, BestKeeper, ΔCt method, NormFinder and RefFinder. The results indicate that UBC-E2 and UBQ5 can be used as reference genes in all samples and softwares evaluated. The genes β-tubulin and eIF-4α, traditionally used as reference genes, along with GAPDH, presented lower stability values. The gene expression of basic leucine zipper (bZIP23 and bZIP72) was used to validate the selected reference genes, demonstrating that the use of an inappropriate reference can induce erroneous results.

Entities:  

Keywords:  Oryza sativa L.; Real-time quantitative PCR; RefFinder; UBC-E2; UBQ5

Mesh:

Substances:

Year:  2016        PMID: 27878453     DOI: 10.1007/s13353-016-0374-1

Source DB:  PubMed          Journal:  J Appl Genet        ISSN: 1234-1983            Impact factor:   3.240


  32 in total

1.  Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method.

Authors:  K J Livak; T D Schmittgen
Journal:  Methods       Date:  2001-12       Impact factor: 3.608

2.  Guideline to reference gene selection for quantitative real-time PCR.

Authors:  Aleksandar Radonić; Stefanie Thulke; Ian M Mackay; Olfert Landt; Wolfgang Siegert; Andreas Nitsche
Journal:  Biochem Biophys Res Commun       Date:  2004-01-23       Impact factor: 3.575

3.  Selection of appropriate reference genes for gene expression studies by quantitative real-time polymerase chain reaction in cucumber.

Authors:  Hongjian Wan; Zhenguo Zhao; Chuntao Qian; Yihu Sui; Ahmed Abbas Malik; Jinfeng Chen
Journal:  Anal Biochem       Date:  2009-12-11       Impact factor: 3.365

4.  How to do successful gene expression analysis using real-time PCR.

Authors:  Stefaan Derveaux; Jo Vandesompele; Jan Hellemans
Journal:  Methods       Date:  2009-12-05       Impact factor: 3.608

5.  Comparative transcriptional profiling of two contrasting rice genotypes under salinity stress during the vegetative growth stage.

Authors:  Harkamal Walia; Clyde Wilson; Pascal Condamine; Xuan Liu; Abdelbagi M Ismail; Linghe Zeng; Steve I Wanamaker; Jayati Mandal; Jin Xu; Xinping Cui; Timothy J Close
Journal:  Plant Physiol       Date:  2005-09-23       Impact factor: 8.340

6.  A soybean (Glycine max) polyubiquitin promoter gives strong constitutive expression in transgenic soybean.

Authors:  Carlos M Hernandez-Garcia; Adriana P Martinelli; Robert A Bouchard; John J Finer
Journal:  Plant Cell Rep       Date:  2009-02-20       Impact factor: 4.570

7.  Selection of internal control genes for quantitative real-time RT-PCR studies during tomato development process.

Authors:  Marino Expósito-Rodríguez; Andrés A Borges; Andrés Borges-Pérez; José A Pérez
Journal:  BMC Plant Biol       Date:  2008-12-22       Impact factor: 4.215

8.  A quantitative RT-PCR platform for high-throughput expression profiling of 2500 rice transcription factors.

Authors:  Camila Caldana; Wolf-Rüdiger Scheible; Bernd Mueller-Roeber; Slobodan Ruzicic
Journal:  Plant Methods       Date:  2007-06-08       Impact factor: 4.993

9.  Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes.

Authors:  Jo Vandesompele; Katleen De Preter; Filip Pattyn; Bruce Poppe; Nadine Van Roy; Anne De Paepe; Frank Speleman
Journal:  Genome Biol       Date:  2002-06-18       Impact factor: 13.583

10.  Selection of suitable reference genes for assessing gene expression in pearl millet under different abiotic stresses and their combinations.

Authors:  Radha Shivhare; Charu Lata
Journal:  Sci Rep       Date:  2016-03-14       Impact factor: 4.379

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  7 in total

1.  Identification and validation of superior housekeeping gene(s) for qRT-PCR data normalization in Agave sisalana (a CAM-plant) under abiotic stresses.

Authors:  Muhammad Bilal Sarwar; Zarnab Ahmad; Batcho Agossa Anicet; Moon Sajid; Bushra Rashid; Sameera Hassan; Mukhtar Ahmed; Tayyab Husnain
Journal:  Physiol Mol Biol Plants       Date:  2020-02-04

2.  Molecular responses to recurrent drought in two contrasting rice genotypes.

Authors:  Priscila Ariane Auler; Marcelo Nogueira do Amaral; Gabriela Dos Santos Rodrigues; Letícia Carvalho Benitez; Luciano Carlos da Maia; Gustavo Maia Souza; Eugenia Jacira Bolacel Braga
Journal:  Planta       Date:  2017-07-12       Impact factor: 4.116

3.  A sensitive synthetic reporter for visualizing cytokinin signaling output in rice.

Authors:  Jinyuan Tao; Huwei Sun; Pengyuan Gu; Zhihao Liang; Xinni Chen; Jiajing Lou; Guohua Xu; Yali Zhang
Journal:  Plant Methods       Date:  2017-10-27       Impact factor: 4.993

4.  Analysis of differential gene expression and alternative splicing is significantly influenced by choice of reference genome.

Authors:  Erin Slabaugh; Jigar S Desai; Ryan C Sartor; Lovely Mae F Lawas; S V Krishna Jagadish; Colleen J Doherty
Journal:  RNA       Date:  2019-03-14       Impact factor: 4.942

5.  Identification and selection of reference genes for gene expression analysis by quantitative real-time PCR in Suaeda glauca's response to salinity.

Authors:  Meng Wang; Tingting Ren; Prince Marowa; Haina Du; Zongchang Xu
Journal:  Sci Rep       Date:  2021-04-21       Impact factor: 4.379

6.  Selection of the optimal reference genes for expression analyses in different materials of Eriobotrya japonica.

Authors:  Wenbing Su; Yuan Yuan; Ling Zhang; Yuanyuan Jiang; Xiaoqing Gan; Yunlu Bai; Jiangrong Peng; Jincheng Wu; Yuexue Liu; Shunquan Lin
Journal:  Plant Methods       Date:  2019-01-28       Impact factor: 4.993

7.  Validation of Reference Genes for Studying Different Abiotic Stresses in Oat (Avena sativa L.) by RT-qPCR.

Authors:  Judit Tajti; Magda Pál; Tibor Janda
Journal:  Plants (Basel)       Date:  2021-06-22
  7 in total

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